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ALKA Selects SPSS Predictive Analytics

Originally published February 23, 2006

SPSS, a provider of predictive analytics software, recently announced that Danish insurance company ALKA is fighting customer fraud and enhancing customer services with SPSS’ Predictive Claims application. ALKA recently purchased and implemented the software to improve claim handling efficiency while reducing the cost of fraudulent claims.

ALKA differentiate itself in a highly competitive market, the company aimed to optimize its expensive claim handling processes and offer better service to customers. ALKA sought to enable “fast-track claim handling” while still sifting out the fraudulent cases from its high claim volumes. Industry experts estimate that on average 10 percent of all claims are fraudulent, whereas usually only 0.5 percent to 1 percent of fraud is actually being detected.

SPSS’ software now enables ALKA to automatically determine during the claim notification process whether an incoming claim qualifies for immediate approval or needs to be further examined by experts. Hence, the company is now able to settle 8 out of 10 claims immediately within 24 hours after the notification, reducing claim cycle times and providing optimal customer service.

“We want to ensure that our honest and loyal customers are presented with good prices. To accomplish this, we must reduce fraud and SPSS helps us realize this,” said Jakob Laursen, Vice President of business intelligence at ALKA.

SPSS’ Predictive Claims works in real time, meaning that when a claim is reported in the call center, the system automatically provides an assessment of the likelihood of fraud. The call center agent can then use this information to accept a legitimate claim quickly or forward a suspicious claim internally for further investigation.

This BeyeNETWORK news item contains information from a recent press release by the company mentioned.